New York and Toronto Novels after Postmodernism: Explorations of the Urban
Bibliographic record
Abstract
Cities are material and symbolic spaces through which nations define their cultural identities. The great cities that have arisen on the North American continent have stimulated the imaginations of the United States and Canada in very different ways. This first comparative study of North American urban fiction starts out by delineating the sociohistorical and literary contexts in which cities grew into diverging symbolic spaces in American and Canadian culture. After an overview of recent developments in the cultural conception of urban space, the book takes New York and Toronto fiction as exemplary for exploring representations of the urban after postmodernism. It analyzes four twenty-first-century novels: two set in New York - Siri Hustvedt's 'What I Loved' and Paule Marshall's 'The Fisher King' - and two set in Toronto - Carol Shields's 'Unless' and Dionne Brand's 'What We All Long For.' While these texts continue to echo the specific traditions of nation building and canon formation in the United States and Canada, they also share certain features. All of them investigate the affective crossroads of the city while returning to a more realistic mode of representation. Caroline Rosenthal is Professor of American Literature at the Friedrich-Schiller University in Jena, Germany
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".